Cancer is a consequence of the mis-expression of genes. The disease is almost always triggered by one or more genetic events that are largely somatic and much less often due to the inheritance of a single gene disorder. Efforts to identify both heritable and spontaneous nucleotide variants that together confer risk to develop different types of cancer have focused in large part on the ~1.2% of the genome that encodes proteins. Yet protein-coding variation fails to explain most cancer susceptibility. Recent GWAS studies indicate that non-coding regulatory elements account for a large fraction of disease-associated variants, which may explain part of the missing genetic component of the disease. In addition to genetic instability, cancer genomes display widespread changes in DNA methylation, which is thought to be a critical aspect of the gene regulatory mechanisms that maintain cellular identity. Our work has shown that specific patterns of intergenic DNA methylation, and specifically localized hypomethylation, distinguish tissue-specific lineages and the identities of the different cell-types within them. Moreover, profiles of intergenic hypomethylation may be used to index putative cell-type specific enhancer elements across the genome. In this context, we have observed higher methylation variability between individuals at enhancers than other genomic elements. These observations may echo recent GWAS studies in that, like regulatory sequence variation, individual patterns of enhancer methylation may reflect differences in gene regulation and disease susceptibility. Together, these ideas form the basis of my central hypothesis: non-coding regulatory anomalies contribute more to the development of cancer than previously appreciated. The objectives of this proposal are therefore to capture both genetic and epigenetic diversity across the non-coding cancer regulome, to investigate the interplay between sequence plasticity and methylation state and to test the functional impact of this variation on gene regulatory activity. I will build upon reference datasets that I have generated as a postdoctoral fellow, namely in hematopoietic cell- types, to explore these ideas using B cell lymphoma (CLL) as a model. This will be accomplished through three focused aims directed at 1) building regulome catalogues of cell-type specific enhancers through comparative methylation profiling, 2) performing targeted resequencing of regulomes in well-defined models of cancer, and 3) testing the competence of identified enhancer variants to drive gene expression. This information may be used to build quantitative models that predict the impact of regulatory variation on enhancer activity levels and potential effects on target genes. The proposed research will tackle an underexplored area of cancer genomics that will complement current efforts to better understand the molecular basis of cancer.